In the rapidly evolving landscape of technology, "data science" is no longer just about structured databases and traditional statistics. The rise of Large Language Models (LLMs) and Generative AI has fundamentally shifted the industry.
In our Online Master’s in Data Science program, we don't just react to these shifts; we integrate them. Our curriculum is intentionally and thoughtfully updated to stay in step with industry standards, ensuring our students are not just users of AI but architects who apply it responsibly.
1. Programmatic Interaction: LLMs from the Code Up
Beginning in Fall 2025, we introduced new content in our R and Python courses that teaches students to interact directly with LLMs through code.
Using cutting-edge tools like the ellmer package in R (introduced in June 2025 and incorporated into our August classes), students learn how to:
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Programmatically prompt models.
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Process complex AI responses.
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Embed LLM capabilities into reproducible data workflows.
2. Critical Thinking in Machine Learning
In our Introduction to Machine Learning course, students apply LLMs to complement their analytical work. However, the focus remains on critical evaluation. For example, students use LLMs to identify the limitations of specific techniques, such as the pitfalls of using Euclidean distance for geographically distributed data, ensuring they remain the human in the room who understands the why behind the math.
3. Applied Tasks: From Sentiment to Hardware
We believe in learning by doing. In our Behavioral Data Science course, students extend their LLM work to applied tasks, such as advanced sentiment analysis.
Beyond the online classroom, our in-person Immersion Weekends allow us to explore emerging AI applications that don’t fit into a traditional semester schedule. During a recent immersion in Dallas, TX, students leveraged LLMs to assist in writing code for data collection from hardware-based systems, including edge-computing sensors.
4. Mastering the Mechanics
While we focus on modern applications, we never sacrifice the fundamentals. Our students learn exactly how neural networks and transformer architectures are built and function.
A note on our approach: We do not build full LLMs from scratch, as the hardware and time requirements are prohibitive within a 21-month master’s program. Instead, we focus on equipping you with the conceptual understanding and practical skills needed to apply advanced AI tools responsibly and effectively in real-world contexts.
5. Ethics: The Notre Dame Core
Generative AI poses unique challenges related to bias, copyright, and misinformation. Our Ethics for AI and Data Science course challenges students to apply a critical lens to rapidly changing legal landscapes, ensuring they lead the data science for good mission.
We believe that the future of AI is human-centered. By combining technical rigor with a world-class foundation in Ethics and Communication, our students aren't just keeping up with the AI revolution; they are leading it.
Are you ready to be a part of the next cohort of Notre Dame Data Scientists? Check out our upcoming events, email us at datascience@nd.edu, or text us at 574-475-2775.